Machine learning is the ability of a computer to learn without being explicitly programmed to perform some function. Thus, machine learning allows a programmer to initially program an algorithm that can be used to predict responses to data, without having to explicitly program every response to every possible scenario that the computer may encounter. In other words, machine learning uses algorithms that the computer uses to learn from and make predictions regarding to data. Machine learning provides a mechanism that allows a programmer to program a computer for computing tasks where design and implementation of a specific algorithm that performs well is difficult or impossible. To implement machine learning, the computer is initially taught using machine learning models from sample inputs. The computer can then learn from the machine learning model to make decisions when actual data are introduced to the computer.
Some applications utilize machine learning models that are continuously updated based upon received inputs or feedback. For example, a recommendation application may recommend certain products based upon feedback provided by other users. As an example, if users provide feedback indicating that a particular product performs well or performs poorly, the machine learning model can use this input or feedback to assist in making future recommendations. These machine learning models are continuously updated and retrained as new user inputs and feedback are received. This continuous updating allows for the machine learning model to adapt and provide responses that are based upon more current information.